InterMET.digital webinar

Date: On-demand
InterMET.digital webinar
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The latest webinar in our series on the business opportunities of extreme weather & climate change focuses on the value of Artificial Intelligence (or AI) to the application of weather data.

NOTE: this webinar has already taken place. It can now be viewed free of charge by following the link below.

The use of AI in conjunction with high powered computers and massive datasets is helping to revolutionise the accuracy and speed of weather forecasting.

Using AI for forecasting isn't new, but the push to use it more often and in different ways is.

For example, in the rapidly developing renewable energy industry, AI can help increase efficiency and reduce costs, fundamental steps in establishing this market. Other key areas such as transportation, predicting devastating events such as tornados and how climate change facilitates the spread infectious diseases show the value of AI can be enormous.

A significant feature of AI is how it can speed data analysis and so produce highly accurate forecasts more rapidly. Improving an extreme weather prediction by just minutes can save many lives and millions of dollars in property.

From the perspective of the new business opportunities, the application of AI is likely to be an especially fertile area.

In this webinar, our panel of leading experts from industry, academia and the public sector will investigate AI's huge potential when it comes to weather affected enterprises.

Moderator & Chair

  • Dr. Jan Dutton
    CEO of Prescient Weather Ltd.

Panellists

  • Dr. Sue Ellen Haupt
    Senior Scientist, Deputy Director, Research Applications Laboratory, National Center for Atmospheric Research

  • Dr. Amy McGovern
    Lloyd G. and Joyce Austin Presidential Professor, School of Computer Science and School of Meteorology, Director, NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography, University of Oklahoma

  • Florian Pappenberger
    Director of Forecasts, European Centre for Medium-Range Weather Forecasts

  • John Williams
    Senior Manager, Forecasting Sciences, The Weather Company, an IBM Business

This webinar will be of value to:

  • Existing weather-related businesses wanting to know more about the business potential of AI
  • Entrepreneurs, scientists & researchers investigating opportunities in this growing area
  • Existing businesses seeking to diversify into the weather sectors or engaged in areas impacted by weather & climate change
  • Investors wanting to understand the opportunities associated with AI and weather data

Dr. Jan Dutton

Dr. Jan Dutton

CEO, Prescient Weather Ltd

Jan is the CEO of Prescient Weather Ltd. and ClimBiz Ltd. His career spans positions at Weather Ventures, Earth Networks, Storm Exchange, Schneider Electric, and DTN. Dr. Dutton’s career objective is to enable business decision making based on weather and climate information.

He received a dual degree B.A. in Physics and Science and Technology Studies from Colby College in Waterville, ME in 1994. He received a Ph.D. from the Penn State Department of Meteorology in 2000. He also received an MBA from the Smeal College Business at Penn State in 2000. His dissertation focused on the simulation of interannual climate variability using regional climate models.

Dr. Sue Ellen Haupt

Dr. Sue Ellen Haupt

Senior Scientist & Deputy Director RAL, NCAR

Sue Ellen Haupt is an NCAR Senior Scientist and Deputy Director of the Research Applications Laboratory (RAL) of NCAR.  Dr. Haupt leads projects in applications of artificial intelligence, renewable energy prediction, and coupling mesoscale to microscale models.  She is also a Contributing and Founding Director of the World Energy and Meteorology Council (WEMC) and a Fellow of the American Meteorological Society (AMS), where she also serves as Future Commissioner of the Commission on the Weather, Water, Climate Enterprise.

Dr. Haupt is an expert in  applications of artificial intelligence in the environmental sciences, boundary layer meteorology, large scale atmospheric dynamics, renewable energy, dynamical systems, numerical methods, and computational fluid dynamics.

Dr. Amy McGovern

Dr. Amy McGovern

School of Computer Science and School of Meteorology, University of Oklahoma

Full title

Dr. Amy McGovern is Lloyd G. and Joyce Austin Presidential Professor, School of Computer Science and School of Meteorology, Director, NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography, University of Oklahoma.

Bio

Amy leads the NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography.  Changes in weather patterns, oceans, sea level rise, and disaster risk amplify the need for accelerated AI research in the environmental sciences. AI2ES is a convergent, multi-sector NSF Trustworthy AI institute led by the University of Oklahoma that brings together researchers in AI, atmospheric science, ocean science, and risk communication.

Dr McGovern’s Research 

My research focuses on developing and applying machine learning and data mining methods for real-world applications with a special interest in high-impact weather. Much of my current work focuses on weather analytics or physical data science, where my students and I are developing physics-based trustworthy AI methods as well as explainable AI.  We apply these methods to high-impact weather phenomena including tornadoes, hail, severe wind events, flooding, drought, and aircraft turbulence.

To create a top science, technology, engineering, and mathmatics (STEM) workforce, we need a diverse and flexible workforce. Diversity will bring new ideas to the forefront and flexibility is required when technology changes rapidly. I’ve developed K-12 outreach projects to excite students about STEM careers and also actively work on diversity, equity, and inclusion.  

I also direct the Interaction, Discovery, Exploration and Adaptation (IDEA) lab.

Education

  • Ph.D. in Computer Science (May 2002), University of Massachusetts Amherst. Dissertation: Autonomous Discovery of Temporal Abstractions from Interaction with an Environment
  • Committee: Andrew G. Barto (chair), J. Eliot B. Moss, Roderic Grupen, and Neil Berthier
  • M.S. in Computer Science (1998), University of Massachusetts Amherst
  • B.S. (Honors) in Math and Computer Science (minor: Spanish, 1996), Carnegie Mellon University

Florian Pappenberger

Florian Pappenberger

Director of Forecasts, European Centre for Medium-Range Weather Forecasts

Florian Pappenberger leads the Forecast Department at the European Centre For Medium-Range Weather Forecasts. The Forecast Department at ECMWF has a strong customer focus. He is responsible for the 24/7 production of weather forecasts, forecast quality control (verification and diagnostics), development of novel forecast products, applications of weather forecasts such as flood, drought, fire and health forecasts, numerical weather prediction relevant software development, data sales and outreach and training.

Florian has a background in the forecasting of weather driven natural hazards including floods, droughts, windstorms, forest fires and impacts on human health. He has over 10 years of expertise in operational probabilistic forecasting, extreme value statistics and numerical model system development at ECMWF. He was responsible for the development and implementation of the operational centre of the Copernicus Emergency Service - Early Warning Systems (floods). Florian is the author of over 150 scientific publications and has won several scientific awards.

He is a fellow of the Royal Geographical Society and the Royal Meteorological Society and a member of several other professional bodies including HEPEX, British Hydrological Society, EGU, AGU, EMS, AMS. He is on the editorial board of several international journals and regularly advises on international committees including WMO and World Bank.

Dr. John Williams

Dr. John Williams

Senior Manager, Forecasting Sciences, The Weather Company, an IBM Business

John Williams is Senior Scientist - Machine Learning and Senior Manager, Forecasting Sciences at The Weather Company, an IBM Business, where he leads a team of scientists and software engineers who use artificial intelligence and data science in conjunction with meteorological expertise to innovate and reduce to practice methods for creating and verifying state-of-the-art weather forecasts that routinely serve individuals and businesses around the globe, including via the Weather Channel mobile app and weather.com.

Before joining The Weather Company in 2015, John worked as a Project Scientist in the Research Applications Laboratory of the National Center for Atmospheric Research where he led projects funded by the Federal Aviation Administration, the National Aeronautics and Space Administration and private industry to develop decision support systems related to aviation weather detection, nowcasting and forecasting, as well as renewable energy and energy demand forecasting.

John is a member of the Senior Leadership Team for the National Science Foundation’s Artificial Intelligence Institute for Research on Trustworthy AI in Weather, Climate and Coastal Oceanography led by the University of Oklahoma. He previously served on the American Meteorological Society’s Committee on Artificial Intelligence Applications to Environmental Science, including as Chair.

John earned his Ph.D. in Mathematics, M.S. in Applied Mathematics and M.A. in Mathematics from the University of Colorado and his B.A. (Honors) in Physics from Swarthmore College.


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